An advanced public transportation system becomes an indicator for a country. Accordingly, it is essential that the decision-makers (DMs) conduct an initial study based on passengers’ view in order to improve the public transportation services. Since involving multi factors, the problem is often solved using the multi-criteria decision-making (MCDM) approaches. This study aims to examine significant factors on passengers decision making to use public transportation using Fuzzy AHP and DEMATEL. The Fuzzy AHP method is proposed to determine criteria weights so that significant critera are obtained, then the causal relations including the criteria are visualized using DEMATEL. This study demonstrates the integration of the two MCDM methods in a BRT system in the region of Yogyakarta, Indonesia, and invites passengers and the DMs. The result indicated that 21 criteria are identified, while the 11 significant criteria are selected based on the Fuzzy AHP weight – α-cut screening. Besides, the DEMATEL has succeeded in describing the influence relationship for the criteria, where firstly, the significant criteria are classified into cause and effect group and secondly, the two criteria, namely coverage to strategic points and on time arrival, should be put on the top priority list. This study enables the DMs to solve public transportation problems more effectively. However, the follow-up study should be carried out by including other factors such as economic and sustainability to strengthen the decision-making process.

Abstrak— Tujuan dari penelitian ini adalah untuk mengevaluasi kinerja karyawan di sebuah pabrik fitting pipa yang terletak di wilayah Yogyakarta, Indonesia, dengan menggunakan teknik pengambilan keputusan multi kriteria (MCDM). Pabrikan saat ini telah melakukan evaluasi kinerja; namun, ada dua kelemahan dalam penilaian sistem saat ini. Pertama, metode saat ini tidak dapat menentukan prioritas kriteria. Kedua, penilaian pribadi juga mempengaruhi peringkat karyawan, dan oleh karena itu hal ini memungkinkan adanya ambiguitas dalam evaluasi. Dalam penelitian ini diperkenalkan hybrid BWM-Fuzzy TOPSIS untuk mengevaluasi kinerja secara lebih realistis yang melibatkan 15 karyawan. BWM digunakan untuk menentukan bobot kriteria yang terdiri dari tiga kriteria dan sembilan subkriteria, sedangkan Fuzzy TOPSIS untuk pemeringkatan kinerja pegawai. Dengan mensimulasikan model optimasi min-max yang dirumuskan, bobot kriteria optimal dari yang tertinggi hingga yang terendah adalah semangat kerja karyawan (M), efektivitas kerja (E), dan produktivitas kerja (P). Bobot global pada prioritas tertinggi adalah loyalitas karyawan (M2), dan prioritas terendah adalah akurasi pekerjaan (P3). Penelitian ini telah mengevaluasi kinerja karyawan di perusahaan dengan cara yang lebih terstruktur dan dapat diandalkan. Karena secara spesifik dapat mengurutkan yang berkinerja terbaik hingga yang berkinerja terburuk, sedangkan pada metode saat ini, ada sembilan dari 15 karyawan yang tidak dapat diurutkan karena nilai total yang sama. Untuk studi lebih lanjut, analisis sensitivitas dapat dilakukan dengan mensimulasikan berbagai skenario untuk membawa lebih banyak informasi bagi pengambil keputusan ketika berhadapan dengan situasi tertentu. Abstract— The purpose of this study is to evaluate employee performance in a pipe fittings manufacturer situated in the region of Yogyakarta, Indonesia, using multi-criteria decision-making (MCDM) techniques. The manufacturer has currently conducted a performance evaluation; however, there have been two drawbacks in the current system assessment. Firstly, the current method cannot determine the priority of criteria. Secondly, personal judgment has also influenced the employee rankings, and therefore this allows ambiguity on evaluation. In this study, a hybrid BWM-Fuzzy TOPSIS is introduced to more realistically evaluate performance involving 15 employees. BWM is used to determine the weight of the criteria comprising three criteria and nine sub-criteria, while Fuzzy TOPSIS is for ranking employees’ performance. By simulating the formulated min-max optimization models, the optimal criteria weights from the highest to the lowest one are employee morale (M), job effectiveness (E), and job productivity (P), respectively. The global weight at the highest priority is employee loyalty (M2), and the lowest priority is job accuracy (P3). This research has evaluated employee performance in the company in a more structured and reliable way. It is because it can specifically rank the best performer to the worst performer, while in the current method, there have been nine out of 15 employees who cannot be ranked due to similar total value. For further study, a sensitivity analysis can be carried out by simulating various scenarios to bring more information for the decision-makers when dealing with a particular situation.